Male octopuses use a specialized arm called the hectocotylus to navigate inside of the female mantle and toward the ovary to deposit spermatophores for fertilization. The mechanisms determining the success of this strategy have remained unknown. Villar et al. have now demonstrated that progesterone produced in female ovaries activates hectocotylus neural activity and autonomous movement and stimulates male mating search behavior (see the Perspective by Di Cosmo). Sensory cells in the hectocotylus expressing the receptor CRT1 are responsible for sensing progesterone. These results describe the molecular basis of a previously unrecognized sensory organ for mating in octopus and shed light on how sensory innovation determines reproductive success. —Mattia Maroso

Although protein structures can now be accurately predicted, how proteins fold remains unresolved. The convergence of single-molecule experiments and advanced computational tools will enable elucidation of folding pathways and will determine whether folding proceeds through energy funnels, discrete foldons or both. This resolution will define essential mechanisms of protein folding and misfolding.

Protein function often involves multiple conformational states. Several multiple sequence alignment-perturbing strategies, including stochastic subsampling, clustering, and column masking, have been shown to enhance AlphaFold2 (AF2) sampling of alternative protein states. Here, we evaluate these strategies on AlphaFold3 (AF3) and compare their performance with the BioEmu Boltzmann sampling model on 107 proteins with multiple experimentally solved conformational states. We find that unperturbed AF3 samples alternative states with significantly higher TM-scores compared to AF2 and comparable to BioEmu. In particular, all MSA perturbation methods improve AF3 sampling at a statistically significant level, improving the top 1% TM-score by at least 0.05 in approximately 20% of cases each, while rarely worsening the performance. Furthermore, we find that different choices of amino acid masks can improve column-masked AF3 sampling for specific targets. Our results highlight how MSA perturbations remain relevant in AF3, providing a useful tool for understanding dynamic biological processes.

Anesthetics and anticonvulsants act, in part, through diverse populations of type-A ɣ-aminobutyric acid receptors (GABA_ARs) formed from a pool of 19 subunits. In the hippocampus, α5 subunits primarily coassemble with β3 and, in some cases, γ2, generating numerous subtypes with differential functional and pharmacological properties critical in learning and memory. The stoichiometry, structure, and gating of these subpopulations are poorly understood. Here we show using cryogenic electron microscopy and electrophysiology that the human α5β3 GABA_AR predominantly assembles with 2α:3β stoichiometry, though a minority population of 1α:4β indicates multiple assemblies are possible. In a resting-like state, a conserved activation gate and Zn²⁺-coordination at histidines on β3 block ion conduction. Upon GABA binding, global rearrangements release Zn²⁺ and open the activation gate in nearly all receptors. The activated receptor is unaffected upon binding the anesthetic etomidate or anticonvulsant topiramate, supporting a conformational selection mechanism of action. This work thus reveals the assembly, activation, and modulation of a GABA_AR subtype critical to cognition, providing templates for structure-based drug discovery.

GABA_A receptors (GABA_ARs) are the primary inhibitory neurotransmitter receptors throughout the central nervous system. Genetic mutations causing their dysfunction are related to a broad spectrum of human disorders such as epilepsy, neurodevelopment and intellectual disability, autism spectrum disorder, schizophrenia, and depression. GABA_ARs are also important drug targets for anxiolytics, anticonvulsants, antidepressants, and anesthetics. Despite significant progress in understanding their three-dimensional structure, a critical gap remains in determining the molecular basis for channel gating. We recently identified mutations in the M2-M3 linkers that suggest linker flexibility has asymmetric subunit-specific correlations with channel opening. Here we use non-canonical amino acids (ncAAs) to investigate the role of main-chain H-hydrogen bonds (H-bonds) that may stabilize the M2-M3 linkers. We show that a single main-chain H-bond within the β2 subunit M2-M3 linker inhibits pore opening and is required to keep the unliganded channel closed. Furthermore, breaking this H-bond accounts for approximately one third of the energy used to open the channel during activation by GABA. In contrast, the analogous H-bond in the α1 subunit has no effect on gating. Our molecular simulations support the idea that channel opening involves the state-dependent breakage/disruption of a specific main-chain H-bond within the β2 subunit M2-M3 linker.

γ-Aminobutyric acid type A (GABAA) receptors are ligand-gated ion channels in the central nervous system with largely inhibitory function. Despite being a target for drugs including general anesthetics and benzodiazepines, experimental structures have yet to capture an open state of classical synaptic α1β2γ2 GABAA receptors. Here, we use a goal-oriented adaptive sampling strategy in molecular dynamics simulations followed by Markov state modeling to capture an energetically stable putative open state of the receptor. The model conducts chloride ions with comparable conductance as in electrophysiology measurements. Relative to experimental structures, our open model is relatively expanded at both the cytoplasmic (−2′) and central (9′) gates, coordinated with distinctive rearrangements at the transmembrane αβ subunit interface. Consistent with previous experiments, targeted substitutions disrupting interactions at this interface slowed the open-to-desensitized transition rate. This work demonstrates the capacity of advanced simulation techniques to investigate a computationally and experimentally plausible functionally critical of a complex membrane protein yet to be resolved by experimental methods.

Pentameric ligand-gated ion channels (pLGICs) are responsible for the rapid conversion of chemical to electrical signals. In addition to the canonical extracellular and transmembrane domains, some prokaryotic pLGICs contain an N-terminal domain (NTD) of unclear structure and function. In one such case, the calcium-sensitive channel DeCLIC, the NTD appears to accelerate gating; however, its evident flexibility has posed a challenge to model building, and its role in calcium sensitivity is unclear. Here we report cryo-EM structures of DeCLIC in circularized lipid nanodiscs, achieving the highest resolution reported so far, and enabling definition of calcium-binding sites in both the N-terminal and canonical extracellular domains. In addition to the symmetric state, calcium depletion promoted an asymmetric conformation of the NTD, offering a structural rationale for small-angle scattering results. Behavior of these structures in molecular dynamics simulations demonstrated calcium stabilization of the NTD. These features of DeCLIC offer a model system for ion-channel modulation by a flexible accessory domain, potentially conserved in structurally homologous systems across evolution.

Resolving protein-ligand interactions in atomic detail is key to understanding how small molecules regulate macromolecular function. Although recent breakthroughs in cryogenic electron microscopy (cryo-EM) have enabled high-quality reconstruction of numerous complex biomolecules, the resolution of bound ligands is often relatively poor. Furthermore, methods for building and refining molecular models into cryo-EM maps have largely focused on proteins and may not be optimized for the diverse properties of small-molecule ligands. Here, we present an approach that integrates artificial intelligence (AI) with cryo-EM density-guided simulations to fit ligands into experimental maps. Using three inputs: 1) a protein amino acid sequence, 2) a ligand specification, and 3) an experimental cryo-EM map, we validated our approach on a set of biomedically relevant protein-ligand complexes including kinases, GPCRs, and solute transporters, none of which were present in the AI training data. In cases for which AI was not sufficient to predict experimental poses outright, integration of flexible fitting into molecular dynamics simulations improved ligand model-to-map cross-correlation relative to the deposited structure from 40-71% to 82-95%. This work offers a straightforward pipeline for integrating AI and density-guided simulations to model building in cryo-EM maps of ligand-protein complexes.

The family of ρ-type GABA_A receptors includes potential therapeutic targets in several neurological conditions, and features distinctive pharmacology compared to other subtypes. Here we report four cryo-EM structures with previously unresolved ligands, electrophysiology recordings, and molecular dynamics simulations to characterize binding and conformational impact of the drugs THIP (a non-opioid analgesic), CGP36742 (a phosphinic acid) and GABOB (an anticonvulsant) on a human ρ1 GABA_A receptor. A distinctive binding pose of THIP in ρ1 versus α4β3δ GABA_A receptors offers a rationale for its inverse effects on these subtypes. CGP36742 binding is similar to the canonical ρ-type inhibitor TPMPA, supporting a shared mechanism of action among phosphinic acids. Binding of GABOB is similar to GABA, but produces a mixture of partially-locked and desensitized states, likely underlying weaker agonist activity. Together, these results elucidate interactions of a ρ-type GABA_A receptor with therapeutic drugs, offering mechanistic insights and a basis for further pharmaceutical development.

A diverse set of modulators, including stimulants and anesthetics, regulates ion channel function in our nervous system. However, structures of ligand-bound complexes can be difficult to capture by experimental methods, particularly when binding is dynamic. Here, we used computational methods and electrophysiology to identify a possible bound state of a modulatory stimulant derivative in a cryptic vestibular pocket of a mammalian serotonin-3 receptor. We first applied a molecular dynamics simulation–based goal-oriented adaptive sampling method to identify possible open-pocket conformations, followed by Boltzmann docking that combines traditional docking with Markov state modeling. Clustering and analysis of stability and accessibility of docked poses supported a preferred binding site; we further validated this site by mutagenesis and electrophysiology, suggesting a mechanism of potentiation by stabilizing intersubunit contacts. Given the pharmaceutical relevance of serotonin-3 receptors in emesis, psychiatric, and gastrointestinal diseases, characterizing relatively unexplored modulatory sites such as these could open valuable avenues to understanding conformational cycling and designing state-dependent drugs.